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Open AccessArticle

Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

Institute of Biosystems Engineering, Faculty of Agronomy and Bioengineering, Poznan University of Life Sciences, ul. Wojska Polskiego 28, 60-637 Poznan, Poland
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Agriculture 2020, 10(4), 112; https://doi.org/10.3390/agriculture10040112
Received: 12 February 2020 / Revised: 26 March 2020 / Accepted: 1 April 2020 / Published: 4 April 2020
(This article belongs to the Special Issue Image Analysis Techniques in Agriculture)
This paper describes the research aimed at developing an effective quality assessment method for potato tubers using neural image analysis techniques. Nowadays, the methods used to identify damage and diseases are time-consuming, require specialized knowledge, and often rely on subjective judgment. This study showed the use of the developed neural model as a tool supporting the evaluation of potato tubers during the sorting process in the storage room. View Full-Text
Keywords: artificial neural network; image analysis; potato tubers quality; neural classification artificial neural network; image analysis; potato tubers quality; neural classification
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Przybylak, A.; Kozłowski, R.; Osuch, E.; Osuch, A.; Rybacki, P.; Przygodziński, P. Quality Evaluation of Potato Tubers Using Neural Image Analysis Method. Agriculture 2020, 10, 112.

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